Installation#

Python version 3.9 or newer is recommended. Warp can run on x86-64 and ARMv8 CPUs on Windows, Linux, and macOS. GPU support requires a CUDA-capable NVIDIA GPU and driver (minimum GeForce GTX 9xx).

The easiest way to install Warp is from PyPI:

$ pip install warp-lang

Installing from GitHub Releases#

The binaries hosted on PyPI are currently built with the CUDA 12 runtime. We also provide binaries built with the CUDA 11.8 runtime on the GitHub Releases page. Copy the URL of the appropriate wheel file (warp-lang-{ver}+cu11-py3-none-{platform}.whl) and pass it to the pip install command, e.g.

Platform

Install Command

Linux aarch64

pip install https://github.com/NVIDIA/warp/releases/download/v1.5.0/warp_lang-1.5.0+cu11-py3-none-manylinux2014_aarch64.whl

Linux x86-64

pip install https://github.com/NVIDIA/warp/releases/download/v1.5.0/warp_lang-1.5.0+cu11-py3-none-manylinux2014_x86_64.whl

Windows x86-64

pip install https://github.com/NVIDIA/warp/releases/download/v1.5.0/warp_lang-1.5.0+cu11-py3-none-win_amd64.whl

The --force-reinstall option may need to be used to overwrite a previous installation.

CUDA Requirements#

  • Warp packages built with CUDA Toolkit 11.x require NVIDIA driver 470 or newer.

  • Warp packages built with CUDA Toolkit 12.x require NVIDIA driver 525 or newer.

This applies to pre-built packages distributed on PyPI and GitHub and also when building Warp from source.

Note that building Warp with the --quick flag changes the driver requirements. The quick build skips CUDA backward compatibility, so the minimum required driver is determined by the CUDA Toolkit version. Refer to the latest CUDA Toolkit release notes to find the minimum required driver for different CUDA Toolkit versions (e.g., this table from CUDA Toolkit 12.6).

Warp checks the installed driver during initialization and will report a warning if the driver is not suitable, e.g.:

Warp UserWarning:
   Insufficient CUDA driver version.
   The minimum required CUDA driver version is 12.0, but the installed CUDA driver version is 11.8.
   Visit https://github.com/NVIDIA/warp/blob/main/README.md#installing for guidance.

This will make CUDA devices unavailable, but the CPU can still be used.

To remedy the situation there are a few options:

  • Update the driver.

  • Install a compatible pre-built Warp package.

  • Build Warp from source using a CUDA Toolkit that’s compatible with the installed driver.

Dependencies#

Warp supports Python versions 3.8 onwards, with 3.9 or newer recommended for full functionality. Note that some optional dependencies may not support the latest version of Python.

NumPy must be installed.

The following optional dependencies are required to support certain features:

Building from Source#

For developers who want to build the library themselves the following tools are required:

After cloning the repository, users should run:

$ python build_lib.py

Upon success, the script will output platform-specific binary files in warp/bin/. The build script will look for the CUDA Toolkit in its default installation path. This path can be overridden by setting the CUDA_PATH environment variable. Alternatively, the path to the CUDA Toolkit can be passed to the build command as --cuda_path="...". After building, the Warp package should be installed using:

$ pip install -e .

The -e option is optional but ensures that subsequent modifications to the library will be reflected in the Python package.

Conda Environments#

Some modules, such as usd-core, don’t support the latest Python version. To manage running Warp and other projects on different Python versions one can make use of an environment management system such as Conda.

Warning

When building and running Warp in a different environment, make sure the build environment has the same C++ runtime library version, or an older one, than the execution environment. Otherwise Warp’s shared libraries may end up looking for a newer runtime library version than the one available in the execution environment. For example, on Linux this error could occur:

OSError: <...>/libstdc++.so.6: version `GLIBCXX_3.4.30' not found (required by <...>/warp/warp/bin/warp.so)

This can be solved by installing a newer C++ runtime version in the runtime Conda environment using conda install -c conda-forge libstdcxx-ng=12.1 or newer.

Alternatively, the build environment’s C++ toolchain can be downgraded using conda install -c conda-forge libstdcxx-ng=8.5. Or, one can activate or deactivate Conda environments as needed for building vs. running Warp.